Detection Character Regions and Comparison Features in Event flyer Images based on Machine Learning

Ken Orimoto, Tomoko Tateyama, Masashi Honda, Takumi Miyamoto, Shimpei Matsumoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Tame-map is a smartphone application that allows users to easily share regional events information within their daily lives by uploading digital flyer images on the web. Although there are a lot of event flyer images uploaded daily, these data have been organized manually. This manual work is hard and takes a huge time, so a system to automate the manual work has been required. An automatic processing method will support the organization, such as categorization, assigning keywords to each image. To develop a basis of automatic flyer images processing, this paper examines detection character region in event flyer images based on machine learning. Concretely, we compared the two features which are obtained vectors based on unsupervised/supervised leanings, such as k-means and SVM respectively.

Original languageEnglish
Title of host publicationProceedings - 2020 9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020
EditorsTokuro Matsuo, Kunihiko Takamatsu, Yuichi Ono, Sachio Hirokawa
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages602-607
Number of pages6
ISBN (Electronic)9781728173979
DOIs
Publication statusPublished - 09-2020
Externally publishedYes
Event9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020 - Kitakyushu, Japan
Duration: 01-09-202015-09-2020

Publication series

NameProceedings - 2020 9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020

Conference

Conference9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020
Country/TerritoryJapan
CityKitakyushu
Period01-09-2015-09-20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management

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